Showing 1-5 of 9 uncategorized:
Mapping the full patient journey in rheumatology: RWD and AI in Action

Rheumatologic diseases like systemic lupus erythematosus (SLE), ankylosing spondylitis, and rheumatoid arthritis can present significant challenges for biopharma. These conditions are chronic, complex, and multisystemic. While traditional clinical trials provide essential insights, they often fail to capture the full spectrum of patient experiences or reflect the diversity seen in real-world populations. Real-world data (RWD), combined[…]

Real-World Evidence and the Five Vs (Velocity, Volume, Variety, Veracity, and Value)

By Vadim Pinsky, PhD, and Gabe Goldfeder, M.A. One of the key frameworks for understanding data analytics in Real-World Evidence (RWE) is the “Five Vs”: Velocity, Volume, Variety, Veracity, and Value. Each aspect plays a crucial role in the data collection and analysis process, shaping how efficiently and accurately insights are generated. For healthcare professionals,[…]

Enhancing Patient Journeys in Clinical Research with AI-Phenotyping

Understanding the patient journey has become crucial for improving treatment outcomes and addressing unmet needs. Pharmaceutical companies need deeper insights into the patient experience — from initial symptoms through diagnosis, treatment, and long-term management – to improve market visibility and marketing opportunities, demonstrate the value of treatments and treatment effectiveness, and ensure the right patients[…]

Leveraging AI to Amplify PHQ-9 Endpoint Availability for Improving Depression Research

By OM1   |   July 16, 2024 When dealing with depression research, accurate real-world data is crucial to demonstrate real-world effectiveness. But what happens when critical data is buried in unstructured clinical notes? And how can we leverage real-world data sources for outcomes research when less than a third of all psychiatry and mental health practices[…]

Integrated Real-World Evidence Generation for Regulatory and Other Research

By Richard Gliklich, MD, CEO, OM1  |   May 22, 2023 Integrated evidence generation (IEG) is a framework for generating evidence to support decision-making in healthcare. It involves the integration of multiple sources of real-world data (RWD), including electronic health records (EHR), claims data, and patient-generated data, to provide a more comprehensive and accurate view of[…]